Modeling of Robot Availability for the Network-controllable Production System

Abstract

An emerging trend in production is the seamless integration of information technology into various aspects of manufacturing processes. Using a host of sensors and communications technology, a multitude of information is collected and utilized in real-time. Such situation allows the companies to operate more efficiently with less cost. A smart use of information is becoming a key factor in brining up the operational competitiveness of many companies. One of the critical information in production is the availability of important equipment for the intended production activities. Accurate estimation of system availability allows less delay and enhanced efficiency in production. The real-time monitoring of equipment conditions and subsequent adjustment of availability in accordance with the evolving production phases enable the realization of benefits the concurrent engineering (CE) is designed for. In this context, this study investigates the probabilistic predictive modeling of robot availability based on the queuing theory, which is integrated into the operation of network-controllable production system with the notion of CE. Substantiated by the real-time data handling and collection, this study suggests the practical and novel approach to help improve the operational efficiency of networked production system.